Autonomous vehicle manufacturers and infrastructure mapping companies can now bring disparate LiDAR data sets together into one super massive point cloud with no control points allowing for rapid and inexpensive regional scale mapping

Civil Maps has completed a major milestone in the drive for rapid regional and continental scale mapping. Using its proprietary artificial intelligence and parallel computing technology, the company has taken multiple data sets for Palo Alto California that were collected over the past several months and fused them together into one super massive point cloud (SMPC) totaling 1 TB, with another 20 TB awaiting processing.

Their processing technology then registered that point cloud to 3 – 5 cm relative accuracy and greater than 1 m absolute accuracy without using a single control point. Covering an area of roughly 60 km2, this is an extraordinary feat. From the company’s calculations, if just a few control points were provided for the entire city, the relative and absolute accuracy would reach near survey grade.

“After achieving this registration milestone, our next step is testing our accuracy.” Said Anuj Gupta, Business Strategist and Co-Founder. “We are currently in the process of hiring a local surveyor to manually survey sample areas so we can compare our results with the real world.”

As described by CEO and Co-Founder, Sravan Puttagunta “One of the big challenges for evolving the autonomous vehicle industry has been the inability of current processing systems to bring together and register massive point clouds. To process point clouds in a block-by-block or street by street method isn’t scalable to the degree needed to map the world for autonomous vehicles and keep it current. The only way to overcome this challenge is to use advance computing techniques and register datasets together as super massive point clouds, as we have done with Palo Alto.”

Civil Maps is putting the finishing touches on its data exchange and processing modules. Once complete, data, whether crowdsourced from vehicles, or provided by survey and remote sensing companies, can be automatically uploaded to the software-as-a-service environment and processed. Registered point clouds will be provided back to end clients or carried forward for use in additional services by Civil Maps, such as their automated feature extraction to produce large regional GIS databases of infrastructure, or 3D models for use in various applications. Regardless of the end product, Civil Maps is streamlining the post processing method and drastically lowering the cost and timeline.

“The capability to rapidly and very accurately register super massive point clouds has far reaching implications.” Joseph Hlady, Head of Sales, Engineering, Environment and Infrastructure. “It is vital to the progress of the autonomous vehicle and machine industries, but also will have a profound impact on the mapping world. We only really started marketing our AI and parallel processing services to the engineering, environment, and infrastructure market this past January, and already we have had considerable interest in our services. We have already completed several projects and are now beginning to work on regional scale mapping projects. By lowering the cost of post processing, we have also lower the barrier to entry for using LiDAR on small engineering projects. This registration service is a great compliment to those other services.”

Civil Maps will be presenting about this new capability at the up coming ESRI User Conference in San Diego June 27 – 30th, with updates coming out during July as the service is fully commercialized and made publicly available. Companies or government organizations with plans for LiDAR programs should consider using this service to lower costs and reduce delivery times of LiDAR products. Civil Maps encourages planners to include the company’s services in discussions and planning as early as possible to ensure that data is collected and delivered to the best standard and well prepared for use in Civil Maps’ technology.

Anyone interested in learning more Civil Maps service and how it might streamline customer mapping services should contact Civil Maps at info@civilmaps.com.

Road infrastructure and makings extracted from the super massive point cloud.